{"url":"/dataset/clipshots","name":"ClipShots","full_name":null,"description_markdown":"**ClipShots** is a large-scale dataset for shot boundary detection collected from Youtube and Weibo covering more than 20 categories, including sports, TV shows, animals, etc. In contrast to previous shot boundary detection datasets, e.g. TRECVID and RAI, which only consist of documentaries or talk shows where the frames are relatively static, ClipShots contains moslty short videos from Youtube and Weibo. Many short videos are home-made, with more challenges, e.g. hand-held vibrations and large occlusion. The types of these videos are various, including movie spotlights, competition highlights, family videos recorded by mobile phones etc. Each video has a length of 1-20 minutes. The gradual transitions in the dataset include dissolve, fade in fade out, and sliding in sliding out.\n\nSource: [https://github.com/Tangshitao/ClipShots](https://github.com/Tangshitao/ClipShots)","description_withheld":null,"homepage":"https://github.com/Tangshitao/ClipShots","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/fast-video-shot-transition-localization-with","title":"Fast Video Shot Transition Localization with Deep Structured Models","first_author":"Shitao Tang","url":null},"license":null,"modalities":[],"tasks":[{"name":"Camera shot boundary detection","url":"/task/camera-shot-boundary-detection","datasets_with_task":"/datasets/task/camera-shot-boundary-detection"}],"languages":[],"variants":["ClipShots"],"data_loaders":[{"repo":"https://github.com/Tangshitao/ClipShots","url":"https://github.com/Tangshitao/ClipShots","frameworks":[]}],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/camera-shot-boundary-detection-on-clipshots","task":"Camera shot boundary detection","dataset_variant":"ClipShots","rows":4,"metrics":["F1 score"],"first_row_in_archive_order":{"model":"AutoShot","paper":"/paper/autoshot-a-short-video-dataset-and-state-of-1","metrics":{"F1 score":"78.7"},"code_links":[{"title":"wentaozhu/AutoShot","url":"https://github.com/wentaozhu/AutoShot"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/autoshot-a-short-video-dataset-and-state-of-1","title":"AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection","date":"2023-04-12","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":0,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/transnet-v2-an-effective-deep-network","title":"TransNet V2: An effective deep network architecture for fast shot transition detection","date":"2020-08-11","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":15,"samples_ran":0,"samples_unverified":15,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/fast-video-shot-transition-localization-with","title":"Fast Video Shot Transition Localization with Deep Structured Models","date":"2018-08-13","rows_on_this_dataset":1,"code_links":4,"syntology":null},{"paper":"/paper/large-scale-fast-and-accurate-shot-boundary","title":"Large-scale, Fast and Accurate Shot Boundary Detection through Spatio-temporal Convolutional Neural Networks","date":"2017-05-09","rows_on_this_dataset":1,"code_links":4,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":18,"samples_ran":0,"samples_unverified":18,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":2,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}